Appendix A. Baseline Energy Forecast - NH.gov - The ... · PDF fileAppendix A. Baseline Energy Forecast ... 4 ISO-NE 2013 Regional System Plan –Section 1.2 Overview of the Results

New Hampshire State Energy Strategy

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Appendix A. Baseline Energy Forecast

A.1 Purpose

Navigant developed a baseline forecast in order to describe New Hampshire’s energy future under the

current portfolio of energy policies, plans, and programs at the state, regional, and national level.

Also referred to as the “business as usual” case, it forecasts both energy demand patterns and supply

infrastructure absent any new or amended policies.

A.2 Methodology

Navigant’s forecast methodology followed a three step process, as illustrated in Figure 1: Baseline

Energy Forecast Methodology.

Figure 1: Baseline Energy Forecast Methodology

The baseline energy forecast was developed using publicly available, industry standard sources of

data reported at the national, regional, and state level. When those sources of data did not directly

report at the state level or account for the most recent plans, policies, and regulations affecting New

Hampshire, the forecasts were adjusted and the relevant assumptions documented. A baseline

forecast was prepared for the electric, thermal, and transportation sectors, and broken into the

residential, commercial, and industrial consumer groups as appropriate. The forecast for each sector

captures energy demand, prices, and key changes in infrastructure related to the supply, demand, and

distribution of energy in New Hampshire. The forecast metrics were selected to provide insight into

key drivers of energy consumption within a given sector as well as to facilitate comparisons between

sectors.

A.3 Electric Sector Forecast

New Hampshire’s electric grid is part of a larger network operated by the Independent System

Operator of New England (ISO-NE). ISO-NE is a regional transmission organization (RTO) which

manages the coordinated dispatch of power generation and directs the flow of electricity across the

region's interstate transmission system. In this network, power generated in New Hampshire may

serve electric loads in other states while loads in New Hampshire are served by power generated in

1. Identify Relevant Data

•Publicly Available, Industry Standard Data Sets

•Data at the National, ISO-NE, and NH level

2. Identify Current Plans and Policies

•Current plans, policies, and NH specific information used to shape the forecast

3. Report Meaningful Metrics

•Quantitative indicators of the future state of NH energy

•Presented by sector, sub-sector and fuel

•Common Units


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other states. This regional organization provides grid operators with greater flexibility to meet power

needs than on a state-by-state basis, increasing the overall reliability and efficiency of the system. It is

within this context that New Hampshire’s electric use, production, and policy options must be

considered.

Electric Sector Model

Navigant’s proprietary portfolio optimization model (POM) was used to develop a baseline electric

sector forecast for New Hampshire individually and for the entire ISO-New England territory, in

order to capture the regional nature of supply and demand (as described above) and its impacts on the

dispatch and development of power generation assets over time. The POM optimizes the dispatch of

power generation assets and the build-out of new power generation units, to meet load requirements

and renewable portfolio standards (RPS) while staying within system operating constraints.

The POM relies on input from a variety of publicly available sources of data and existing policies.

The sources of data, existing plans and policies, and reporting metrics developed for and derived from

POM are highlighted below.

Figure 2: Electric Sector Data Sources, Plans & Policies, and Key Metrics

1

Electric Sector Key Assumptions

In addition to the data sources and existing policies listed above, several key assumptions impact the

electric sector model, including:

RPS – Informed by an analysis of the costs of meeting the RPS as currently formulated, the

POM assumes that the costs will be contained through existing mechanisms such as

alternative compliance payments (ACPs) and other state actions such as the Public Utilities

Commission (PUC) making adjustments to requirements for various classes of renewable

energy. The model is agnostic as to the actual mechanism of cost containment, but the end

result is that renewable power generation as currently classified by the PUC is forecasted to

meet between 60 and 90 percent of current RPS targets, depending on the quantity of

Renewable Energy Credits (RECs) sold out of state.

Carbon Prices – The POM assumes a $10/ton tax on CO2 starting in 2018, as proposed by the

EPA. For reference, the carbon price per ton in the most recent RGGI auction was $4.2

Planned Retirements – The model reflects the retirements of the Vermont Yankee nuclear

plant and the Brayton Point coal plant in Massachusetts (both announced in 2013). Other

1 See A.7 Baseline Energy Forecast – Supporting Data for links to primary data sources 2 http://www.rggi.org/docs/Auctions/23/PR030714_Auction23.pdf.

Data Sources

•EIA AEO

•Ventyx Generation and T&D Database

•Energy Velocity

• ISO-NE CELT 2012 Report

•DSIRE

•Navigant Fuel Price Forecast

Plans & Policies

•NH RPS and Off-Ramps

• ISO-NE Regional System Plan 2012

•EPA Rules for SOx, NOx, and CO2 (proposed 2014): assumes no new coal

•RGGI-New Cap

•Established Contracts (PPAs) for Renewables

Key Metrics

• In-State Capacity (MW)

• Power Generation (GWh and

BBtu)

• Fuel Prices ($/MBtu)

• Wholesale Price ($/kWh)

• Load (GWh and BBtu)

• Peak Load (MW)

• Expenditures ($Million)

• Emissions (MT)


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possible retirements were not modeled. The model assumes that the Seabrook Station nuclear

power plant receives its pending license extension and remains in operation through 2030.

Transmission Expansion – The model assumes new transmission capacity will be constructed

to provide imported power to New England.

Electric Sector Baseline Forecast Results

Using the methodology described above, Navigant’s forecast of power generation infrastructure in

New Hampshire under the “business as usual scenario” is shown in Figure 3: Baseline Forecast of In-

State Power Generation.

Figure 3: Baseline Forecast of In-State Power Generation

3

In the baseline forecast, the utilization of particular power plant technologies is driven primarily by

fuel prices and environmental regulations. In recent years, there has been a substantial reduction of

oil and coal fired power generation in the region.4 Total power generation is expected to remain

predominantly flat over the forecast period, as increasing in-state demand is offset by lower net

exports, which is attributed to increasing energy efficiency in neighboring states.

The forecast shows that 20.1 percent of in-state power generation will come from renewable

resources by 2025, shy of the RPS target of 24.8 percent. This discrepancy may be even greater if the

number of RECs sold out of state is higher than forecast. However, as noted above, the RPS is

structured so that New Hampshire electric providers (utilities and competitive suppliers) can be in

compliance with RPS requirements through the purchase of qualifying RECs from resources

elsewhere in the region, or through the payment of ACPs. In addition, it is important to reiterate that

because New Hampshire is a part of the regional grid, the in-state generation mix is driven in part by

regional needs and policies, such as the forward capacity market and the RPS policies of other states.

3 Baseline forecast of in-state power generation based on Navigant analysis of source data included in A.7 Baseline Energy

Forecast – Supporting Data. 4 ISO-NE 2013 Regional System Plan – Section 1.2 Overview of the Results of System and Strategic Planning Studies

available at: http://www.iso-ne.com/trans/rsp/


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Figure 4: Electric Demand by Sector

5

In contrast to the relatively flat growth of in-state power generation over the forecast period, demand

for electric power in New Hampshire is forecast to rise in all sectors, resulting in lower net exports of

electricity through the forecast period. Electric demand in the residential and commercial sectors is

expected to grow more slowly than in the industrial sector, as increases in population (0.4 percent

annual growth through 20256), housing stock, and commercial building space are offset by modest

gains in appliance and building energy efficiency (recent savings of 0.64 percent annually7). Despite

an economic shift in New Hampshire from manufacturing industries to information technology, the

increasing use of electricity to power equipment (replacing other fuels) is expected to increase

demand in the industrial sector over the forecast period. Electric vehicles are also expected to

contribute to a small increase in demand in the later years of the forecast period.

Despite increasing demand for electricity in New Hampshire, overall emissions associated with power

generation are forecast to remain flat through the remainder of the forecast period as the power

generation mix becomes cleaner. In recent years, emissions have declined considerably in response to

stringent regulations and falling prices for natural gas, which resulted in the retirement of coal-fired

power plants in favor of increased regional usage of cleaner-burning gas. In light of the regional

nature of energy distribution across ISO-NE, New Hampshire’s emissions from power generation are

estimated as a weighted share of total regional emissions, based on the state’s share of regional

electricity demand. The resulting emissions forecast is shown in Figure 5: Emissions from Electric

Power Generation.

5 Baseline forecast of electric demand by sector based on Navigant analysis of source data included in A.7 Baseline Energy

Forecast – Supporting Data. 6 http://www.nh.gov/oep/data-center/population-projections.htm 7 http://www.aceee.org/files/pdf/state-sheet/2013-spending-and-savings-tables.pdf


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Figure 5: Emissions from Electric Power Generation

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Although New Hampshire may have little impact on total regional emissions, reducing in-state

demand through energy efficiency and the use of distributed resources represents a valuable

opportunity to reduce emissions that is within the control of the state’s policymakers, residents, and

businesses.

The interconnected nature of power generation and demand between states in the region, including

the interplay between state’s RPS policies, REC pricing, and ACPs, can have a profound impact on

the mix of New Hampshire’s in-state power generation. For this reason, it is critical for New

Hampshire to continue its active participation in the regional markets at the regional level.

Additionally, efforts to promote reduce demand through energy efficiency and as well as promoting

the use of smaller, distributed resources are both represent opportunities to reduce emissions that are

well within the control of the state’s policymakers, residents, and businesses.

A complete collection of charts detailing the baseline electric forecast can be found in A.7 Baseline

Energy Forecast – Supporting Data.

A.4 Thermal Sector Forecast

Thermal Sector Model

The thermal sector forecast relied heavily on the US Department of Energy (DOE) Energy

Information Administration (EIA) State Energy Data Set (SEDS) and Annual Energy Outlook (AEO).

The forecast was further informed by gas utilities, home heating oil (HHO) distributors, geothermal

installers, and those involved with wood pellet heating programs. For the portion of the thermal

8 Baseline forecast of emissions from electric power generation based on Navigant analysis of source data included in A.7

Baseline Energy Forecast – Supporting Data.


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sector that relies on electricity as an energy source, the forecast used information from the US DOE

Building Energy Data Book to identify the fraction of residential and commercial electric demand

attributed to thermal applications including space heating, water heating, and cooking.

The data sources, existing programs, and key metrics are listed in Figure 6: Thermal Sector Data

Sources, Plans & Policies, and Key Metrics.

Figure 6: Thermal Sector Data Sources, Plans & Policies, and Key Metrics

9

Thermal Sector Key Assumptions

In addition to the data sources and existing plans and policies listed above, several key assumptions

impact the thermal sector model. These include:

Expansion of Natural Gas Distribution – Based on information from New Hampshire’s gas

utilities, minimal additional expansion of conventional natural gas distribution infrastructure

is expected over the forecast period. Additionally, trucked delivery of natural gas to off-main

customers via a “virtual pipeline” is not expected to represent an appreciable quantity of

thermal fuel consumption through the forecast period, though the service is expanding in the

state.

Current Levels of Thermal Electrification – The DOE Building Energy Data Book reports the

breakdown of thermal demand by application and fuel type (electric and other thermal fuels)

on a national level. Given the low market penetration of advanced electric thermal

technologies (including both air source and ground source heat pumps), it was assumed that

this breakdown is a reasonable estimate for New Hampshire and as such was not changed.

Thermal Sector Baseline Forecast Results

In reaction to increasing fuel prices, thermal energy consumption is forecast to decline in the

residential sector owing to gains in energy efficiency. The decline is the greatest for those who use oil

heat, and is enabled by fuel switching (primarily to wood) and through the implementation of high

efficiency retrofits. Though not as pronounced, demand for oil heat in the commercial sector is also

expected to decline over the forecast period. However, in contrast to the residential sector, this

decline is more than offset by an increase in the consumption of natural gas due to anticipated growth

in the commercial sector in on-main areas. Overall demand for thermal energy in the industrial sector

is forecast to remain flat.

9 See A.7 Baseline Energy Forecast – Supporting Data for links to primary data sources

Data Sources

•EIA AEO

•EIA SEDS

•BEA

•DSIRE

•DOE EERE

•DOE Buidling Energy Data Book

•Natural Gas & HHO Distribution Interviews

Plans & Policies

•NH RPS (Thermal Carve-out)

•CORE NH Energy Efficiency Programs

•NH incentives for biomass, solar, and geothermal

Key Metrics

• Consumption (BBtu)

• Fuel Price ($/MBtu)

• Expenditures ($Million)

• Emissions (MT)


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Figure 7: Thermal Energy Consumption by Sector

10

10 Baseline forecast of thermal energy consumption by sector based on Navigant analysis of source data included in A.7



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Figure 8: Thermal Fuel Expenditures by Sector

11

As shown in Figure 7 and Figure 8, despite flat demand for thermal energy through the forecast

period, rising fuel prices are forecast to contribute to substantially higher overall thermal energy

expenditures. New Hampshire has little ability to influence fuel prices, but should help contain these

rising costs by investing in efficiency and small-scale distributed resources. This will provide

residents and businesses in New Hampshire with greater flexibility in meeting their home and

business thermal needs and protection from future fuel price volatility.

A complete collection of charts detailing the baseline thermal energy forecast can be found in A.7


11 Baseline forecast of thermal fuel expenditures by sector based on Navigant analysis of source data included in A.7



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A.5 Transportation Sector Forecast

Transportation Sector Model

To forecast the fuel consumption profile for the transportation sector, Navigant used a rolling stock

model of New Hampshire’s overall fleet, tracking changes in demographics, vehicle price projections,

and available technology. This model relied in part on vehicle registrations from the US and NH

Departments of Transportation, fuel consumption information from the EIA AEO, the National

Highway Traffic Safety Administration (NHTSA) Summary of Fuel Economy Performance, and

information on available transportation technology from DOE’s Office of Energy Efficiency &

Renewable Energy (EERE). This model was used in concert with the vehicle miles traveled (VMT)

forecast for the state which relied on data from the Federal Highway Administration’s (FHWA)

Traffic Volume Trends database, historic and forecasted population from New Hampshire’s Office of

Energy and Planning (OEP), and gross state product data from the Bureau of Economic Analysis

(BEA).

A complete list of data sources, plans & policies, and key metrics for the transportation sector is

shown in Figure 9: Transportation Sector Data Sources, Plans & Policies, and Key Metrics.

Figure 9: Transportation Sector Data Sources, Plans & Policies, and Key Metrics

12

Transportation Sector Key Assumptions

In addition to the data sources and existing policies listed above, several key assumptions impact the

transportation sector model. These include:

Recent trends in the relationship between VMT, population growth, and economic activity

continue through the forecast period. Correcting for recent periods of economic fluctuation

as derived from the Bureau of Economic Analysis (BEA), Navigant identified a small but

upward trend (0.1 percent) for growth in per capita VMT.

The price premium for alternative fuel vehicles (AFVs) – The price premium for AFV’s is

based on a survey of prices for AFVs and their incremental upfront cost relative to industry

counterpart conventional fuel (gasoline powered) vehicles. Based on recent trends in price

premiums, Navigant assumes a decline in this price premium at a rate of 5 percent annually

over the forecast period.

Transportation Sector Baseline Forecast Results

Nearly 90 percent of New Hampshire’s fleet is comprised of light duty gasoline powered vehicles.

The fuel economy of this segment, determined by federal corporate average fuel economy (CAFE)

12 See A.7 Baseline Energy Forecast – Supporting Data for links to primary data sources

Data Sources

•EIA AEO

•DSIRE

•NHSTA

•FHWA

•BEA

•DOE EERE

•US and NH DOT

Plans & Policies

•EPA CAFE Standards

•EPA Ethanol Mandate

•EV Tax Credits

•NH incentives for AFVs

Key Metrics

•Fuel Economy (MPG and MPGe)

•Expenditures ($Million)

•Price ($/MBTU)

•Fuel Consumption (BBTU)

•Emissions (MT)

•Vehicle Miles Traveled (VMT)


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standards, represents the single largest driver affecting energy consumption and emissions in the

transportation sector. Modest increases in fuel economy over the forecast period are shown in Figure

10: Transportation Fleet Average Fuel Economy.

Figure 10: Transportation Fleet Average Fuel Economy

13

The second largest driver affecting energy consumption and emissions is the use of plug-in electric

vehicles. Plug-in electric vehicles dominate the alternative fuel vehicle (AFV) category in the

baseline forecast, but only account for a small fraction (7.5 percent) of total vehicle miles traveled by

the end of the 20-year forecast period as shown in Figure 11: Transportation Sector Vehicle Miles

Traveled.

13 Baseline forecast of transportation fleet average fuel economy based on Navigant analysis of source data included in A.7



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Figure 11: Transportation Sector Vehicle Miles Traveled

14

Despite the improvement in light duty vehicle fuel economy, the modest adoption of alternative fuel

vehicles over the forecast period, and the small increase in overall vehicle miles traveled, the total

fuel related expenditures are still forecast to rise substantially, topping $3 billion in 2028 (see Figure

12: Transportation Sector Fuel Expenditures).

14 Baseline forecast of transportation sector vehicle miles traveled based on Navigant analysis of source data included in A.7



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Figure 12: Transportation Sector Fuel Expenditures

15

This is due to the impact of increasing fuel prices on total fuel expenditures through the forecast

period, more than offsetting gains in efficiency. The fuel price-driven increase in expenditures makes

adopting the highest efficiency vehicles and reducing vehicle miles traveled all the more crucial to

managing costs in the transportation sector.

A complete collection of charts detailing the baseline transportation energy forecast can be found in:

A.7 Baseline Energy Forecast – Supporting Data.

15 Baseline forecast of transportation sector fuel expenditures based on Navigant analysis of source data included in A.7



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A.6 Summary of the Baseline Forecast

New Hampshire’s overall demand for electric and thermal energy is constant during the forecast

period, decreasing demand for energy in the transportation sector contributes to an overall decline in

total energy demand across the state (see Figure 13: Per Capita Energy Demand by Sector). However,

the cost of fuel for power generation, thermal energy, and transportation needs is rising. These rising

costs more than offset the decline in demand, leading to higher overall expenditures for consumers

(see Figure 14: Per Capita Energy Expenditures by Sector).

Figure 13: Per Capita Energy Demand by Sector

16

16 Baseline forecast of per capita energy demand by sector based on Navigant analysis of source data included in A.7



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Figure 14: Per Capita Energy Expenditures by Sector

17

These trends are expected to hold throughout the forecast period. In addition to the general upward

trend of fuel prices, fuel price volatility poses an additional challenge. New Hampshire’s aging

building stock, constrained supply infrastructure, and dispersed population make the state especially

vulnerable to short-term price spikes and supply disruptions.

Rising costs and vulnerability to rapid market changes make the goals identified in the energy vision

all the more pressing for New Hampshire.

A complete collection of summary charts detailing the baseline energy forecast can be found in A.7


17 Baseline forecast of per capita energy expenditures by sector based on Navigant analysis of source data included in A.7



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A.7 Baseline Energy Forecast – Supporting Data

Baseline Forecast Source Data and Plans & Policies

Data Sets Web Address

EIA AEO http://www.eia.gov/forecasts/AEO/

BEA http://www.bea.gov/regional/

DOE Building Energy

Data Book http://buildingsdatabook.eren.doe.gov/

DOE AFDC http://www.afdc.energy.gov/

DSIRE http://www.dsireusa.org/

EIA SEDS http://www.eia.gov/state/seds/

Energy Velocity (Ventyx) http://www.ventyx.com/en/solutions/energy-markets

FHWA http://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm

ISO-NE CELT 2012

Report http://www.iso-ne.com/trans/celt/report/

NHSTA http://www.nhtsa.gov/NCSA

Plans &

Policies Web Address

NH RPS http://www.puc.state.nh.us/sustainable%20Energy/Renewable_Portfolio_Standard_

Program.htm

ISO-NE Regional

System Plan 2012 http://www.iso-ne.com/trans/rsp/

EPA Rules for SOx,

NOx, and CO2 http://www.epa.gov/mats/actions.html

RGGI-New Cap http://www.rggi.org/design/overview/cap

NH CORE Efficiency

Programs http://www.puc.state.nh.us/electric/coreenergyefficiencyprograms.htm

EPA CAFE Standards http://www.epa.gov/fueleconomy/regulations.htm

EPA Ethanol Mandate http://www.epa.gov/OTAQ/fuels/renewablefuels/

Federal EV Tax Credits http://www.afdc.energy.gov/laws/law/US/409


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Electric Sector Charts


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Thermal Sector Charts


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Transportation Sector Charts


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Summary Charts


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Appendix B. Energy Vision

B.1 Purpose

The energy vision describes an ideal energy future for New Hampshire. In contrast to the baseline

forecast, which indicates where the state is expected to be absent new or amended policies, an energy

vision serves to define an ambitious, yet realistic, alternative future for New Hampshire. This vision

helps guide recommendations for the state energy strategy.

B.2 Methodology

The energy vision was developed with input from the advisory council in advance of conducting the

resource potential study to keep the vision aspirational, and followed a five step process:

Figure 15: Energy Vision Development Process

Based on topics discussed with the advisory council and information gained through the development

of the baseline energy forecast, Navigant identified eight key factors in defining New Hampshire’s

energy future. The eight factors include:

The efficiency of NH’s building stock and the potential to reduce energy expenditures;

The mix of renewable power generation and use of smaller scale distributed generation

(DG);

Consumer choice and the availability of alternative fuels;

Alternative options in transportation;

Grid modernization efforts;

Regional issues including demand and supply dynamics, and the interrelationship between

the state’s energy needs and policies;

Fuel prices; and

Emissions regulations.

Step 1: Brainstorm to identify the key factors that shape the future state of energy in New Hampshire

Step 2: Identify which factors NH has a strong ability to influence and have a high level of impact

Step 3: Develop continuums that define the extremes of each factor

Step 4: Discuss where each factor should fall on the continuums as they relate to other outcomes including the security, economics, and sustainability of the energy system

Step 5: Focus on the high impact factors that New Hampshire has the greatest ability to influence


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Each of these factors was mapped based on its relative impact on various metrics related to energy

security, economics, and sustainability and the degree to which New Hampshire has the ability to

exercise influence over it. This helps to focus efforts on those factors for which new or amended

policies and strategic goals could have the greatest positive effect. The results of the mapping are

shown in Figure 16: Relative Impact and Influence of Key Factors. For example, regional demand

dynamics and fuel prices have large relative impacts on energy issues in New Hampshire, but New

Hampshire has less influence over those issues than over others that are directly within the state’s

control such as energy efficiency and clean small scale generation (renewable power generation).

Figure 16: Relative Impact and Influence of Key Factors

Navigant elicited feedback from the advisory council and stakeholders on the relative importance of

each key factor and how each factor might look in the future. Each participant was asked to put

themselves in the year 2025 and envision what the energy landscape might look like. The factors were

placed on the continuum as shown in Figure 17: Continuum of Key Factors Included in the Energy

Vision and the draft energy vision was defined as follows.

Figure 17: Continuum of Key Factors Included in the Energy Vision


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B.3 The Draft Energy Vision

Summary

In 2025, consumers are empowered to manage their energy use by taking full advantage of the

information, market mechanisms, energy efficient technologies, diverse fuel sources, and

transportation options available to them. These services extend from the city centers and coastal areas

of Southern New Hampshire to the rural corners of the Western regions and the North Country -

closing the gap in disparity of energy services across the state. The results of these widespread

consumer empowerment initiatives are lower energy bills, greater choice for the consumer, increased

self-reliance, and a cleaner, more sustainable and resilient energy system.

From an economic perspective, New Hampshire’s stable energy policies leverage public funds ten to

one – inspiring investor confidence, creating high quality jobs, and attracting new residents and

businesses to the state. Efficient transit systems help make New Hampshire tourist friendly and the

state’s high efficiency building stock, skilled workforce, and well managed natural resources make it

regionally competitive and help keep dollars in state. As an active participant in New England’s

broader energy economy, in-state suppliers of energy services receive the proper signals to drive their

business decisions toward creating an efficient and secure energy system that delivers cost-effective,

clean energy to all.

Energy Efficiency

Across New Hampshire, many of the newest homes as well as commercial and public buildings

produce as much energy as they consume - putting the state on track to meet a net-zero energy code in

later years. Additionally, many older buildings have benefited from deep energy retrofits, owing to an

informed consumer base that understands what drives their energy bills and appropriately values the

short and long term benefits of higher efficiency homes and businesses. These efforts incorporate the

latest in energy efficient technologies, resulting from flexible policies and diverse market-based

financing mechanisms that allow customers of all income levels to access the technologies they wish

to use. Because of these efforts, every dollar spent on energy in New Hampshire adds value to the

lives of its residents and the prosperity of its businesses.

Grid Modernization

Beyond simply using less energy, many of the energy saving technologies embedded in New

Hampshire’s homes and businesses provide consumers with valuable information about their energy

consumption while protecting their privacy. This gives consumers both peace of mind and the power

to effectively manage their bills and contain costs. By opening lines of communication with grid

operators, consumers may choose to manage their energy themselves or rely on third party providers

of energy management services to respond in real time to changing energy prices and other market

conditions to help them further reduce their energy bills. Access to real time data and open

communications also contribute to greater reliability of New Hampshire’s energy infrastructure,

providing timely information to consumers so that they may plan and respond accordingly to

unanticipated events and help isolate outages.

Renewable Power Generation

In addition to saving energy, many individual households and businesses produce power themselves -

participating in dynamic local energy markets powered by distributed generation. These localized

energy systems provide an additional measure of resilience against grid outages and other supply

disruptions by seamlessly switching between various fuels and stored power. Further, by relying on

renewable resources, they reduce reliance on imported fuels and foster self-sufficiency within


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communities across the state. In 2025, the combination of reduced demand and further development

of diverse renewable power generation assets helps New Hampshire achieve its renewable portfolio

standard target level.

Fuel Choice and Availability

In 2025, the residents and businesses of New Hampshire have many choices in the fuels they use for

power, heat, and transportation. Consumer’s options for home heating are no longer strictly limited

by their geographic location, offering residents greater peace of mind in the face of fluctuating fuel

prices. Additionally, consumers use the diversity of available fuels and the interconnected

relationship of energy used across the electric, thermal, and transportation sectors to their benefit –

storing electricity in the batteries of their electric vehicles, or powering air-source heat pumps with

energy generated from their rooftop solar panels as examples. By embracing a diverse and

interconnected set of energy solutions, these systems promote the self-reliance of both individual

communities and New Hampshire as a whole. The options for both power generation and building

heating are enhanced by a boom in home-grown clean energy from New Hampshire - keeping dollars

in state and reducing pollution.

Transportation Options

In the transportation sector in 2025, widespread vehicle charging infrastructure is the norm across the

state and fueling stations supporting the latest technology and alternative fuels dot the highways.

Using this infrastructure, residents and business take advantage of the many options for electric

vehicles, plug-in hybrids, and other new transportation technologies. Access to these technologies is

granted through creative financing mechanisms and new business models. Walking communities, ride

shares, and enhanced public transit options exist to benefit residents of all ages (including New

Hampshire’s aging population as well as its youth). These options return both time and money to the

communities of New Hampshire and contribute to improved air quality in city centers. New

Hampshire’s public transit options also benefit those visiting the state, ferrying skiers and hikers alike

to the state’s many resorts and abundant outdoor attractions and further bolstering the state’s tourism

industry. Most importantly, residents of New Hampshire get where they need to go without sending

money out of state, or overseas.


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Appendix C. Resource Potential Analysis

C.1 Purpose

Navigant analyzed thirty-two separate demand and supply side resources to help identify the best way

to move from the baseline energy forecast toward the end state defined in the energy vision. This

study informed discussions of policy initiatives by focusing attention on the biggest opportunities for

change that are both economically justified and technologically feasible. The resources analyzed are

categorized as energy efficiency, thermal & transportation fuels, or power generation & energy

infrastructure (illustrated in Figure 18: Demand and Supply Side Energy Resources).

Figure 18: Demand and Supply Side Energy Resources

C.2 Methodology

Like the baseline energy forecast, the resource potential study utilized publicly available sources of

data and existing resource potential studies to estimate the technical, economic, and market potential

of various demand and supply side resources in 2025. The year 2025 was selected to coincide with

the target year of the energy vision and to allow adequate time for resource changeover. For example,

given rates of fleet turnover in the transportation sector, or the required time to permit and build new

power generation assets, it would be unreasonable to suggest significant change in either of these

resources in the span of one year. A time horizon of ten years provides adequate time for changes in

policy to take effect and produce results.

For the purpose of the resource potential study, Navigant focused on the technical and economic

potential as defined by the National Renewable Energy Lab (NREL) and illustrated in Figure 19:

Resource Potential Levels18

.

18 NREL - U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis, July 2012


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Figure 19: Resource Potential Levels

18

Where possible, the technical and economic potential values were taken directly from existing studies

of resource potential. For instances in which direct data was unavailable or out of date, Navigant

calculated the technical and economic potential and documented the underlying assumptions. For the

market potential estimate, Navigant used the projected 2025 values for each resource from the

baseline forecast. This coincides with what is expected of the market absent any amended policies or

new initiatives affecting a given resource. An estimate of the total resource potential was omitted

from the study as constraints on technology largely render this figure unattainable. The data tables

for the resource potential study can be found in C.6 Resource Potential - Supporting Data.

While the technical, economic, and market potential of resources are important, the comparison of

these levels is of particular importance in developing an energy strategy as it not only helps to

identify the biggest opportunities available, but also provides a high level indication of the types of

barriers affecting each resource. For each resource, the difference between the market potential and

economic potential can be attributed to the limitations of policies, regulations, market inefficiency,

and consumer awareness. For example, New Hampshire has not implemented all of the cost-effective

energy efficiency measures that are available for a variety of reasons related to regulatory barriers,

consumer education, and lack of access to financing.

In contrast, the difference between the economic potential and the technical potential can be attributed

to the cost of technology, factoring in the relative price of fuels and competing technologies.

Resources with a large difference between the technical and economic potential, or technical gap,

may present significant opportunities in the future as the cost of technology drops or competing fuel

prices rise. For example, as the cost of solar panels fall, they become more economically accessible,

closing the gap between the economic potential and technical potential. Similarly, as the cost of

gasoline rises, electric vehicles and plug-in hybrids become more economical purchases because the

upfront costs are offset by greater fuel savings.


Page C-3

However, since New Hampshire has little ability to influence fuel prices or the cost of technology, the

technical gap should mostly be a secondary priority for the state. New Hampshire’s first priority

should be addressing the difference between economic potential and market potential, over which the

state has greater control. See Figure 20 for an example interpretation of economic and technical

gaps.

Figure 20: Technical and Economic Potential Overview and Interpretation

C.3 Energy Efficiency Potential

Residential, Commercial, and Industrial Energy Efficiency

The resource potential study of energy efficiency across the residential, commercial, and industrial

sectors relied heavily on a report prepared for the PUC by GDS Associates, Inc., titled “Additional

Opportunities for Energy Efficiency in New Hampshire,” published in January 2009.19

This report

presented the technical, economic, and market potential of energy efficiency gains in 2018. Navigant

calculated the proposed 2018 savings cited in the GDS report as a percentage of demand for the

residential, commercial, and industrial sectors. See Table 1 and Table 2 for the market, economic, and

technical potential for each sector.

Sector Market Potential Economic Potential Technical Potential

Residential 12.5% 20.9% 31.7%

Commercial 9.2% 19.9% 29.8%

Industrial 10.2% 21.2% 24.5%

Table 1: Electric Energy Savings Potential Estimates20

19 http://www.puc.state.nh.us/Electric/GDS%20Report/NH%20Additional%20EE%20Opportunities%20Study%202-19-

09%20-%20Final.pdf 20 Electric and thermal energy savings potential estimates based on Navigant analysis of the baseline forecast and the GDS

Associates, Inc. report titled “Additional Opportunities for Energy Efficiency in New Hampshire,” which is available at:

http://www.puc.state.nh.us/Electric/GDS%20Report/NH%20Additional%20EE%20Opportunities%20Study%202-19-

09%20-%20Final.pdf


Page C-4

Sector Market Potential Economic Potential Technical Potential

Residential 10.7% 18.7% 50.0%

Commercial 7.2% 17.0% 26.4%

Industrial 4.4% 9.0% 11.2%

Table 2: Thermal Energy Savings Potential Estimates20

To estimate the potential savings in 2025, Navigant applied these same percentages to the 2025

demand figures from the baseline energy forecast. This projection hinges on the assumption that

comparable savings can be achieved between 2009 and 2018 (as expressed in the GDS report) and

between 2014 and 2025 (the time horizon for this resource potential study). Several factors could

contribute to comparatively higher or lower savings, including the emergence of higher efficiency

technology or the shrinking residual opportunity for efficiency improvement due to gains made from

2009 to the present. The results of this analysis are presented in Figure 21: Potential for Residential,

Commercial, and Industrial Energy Efficiency.

Figure 21: Potential for Residential, Commercial, and Industrial Energy Efficiency

20

The analysis shows that the residential and commercial sectors offer substantial opportunities for

additional economically justified thermal efficiency. In both sectors, the remaining economic

potential for thermal efficiency is roughly twice that for electric efficiency. This disparity can be

attributed to multiple sources. The primary reason is that New Hampshire uses more than twice (2.4

times) as much thermal energy as it does electric energy. Additionally, the higher upfront costs

associated with high efficiency thermal retrofits, relative to electric efficiency upgrades, makes them

comparatively more challenging investments for many consumers despite shorter payback periods.

What is perhaps most striking about these results is that while the remaining economic potential for

residential and commercial thermal efficiency are of similar size, the additional technical potential in

the residential sector is more than five times that in the commercial sector. The age of housing stock

and the high cost of capital in the residential sector contribute to its sizable technical potential. In

contrast, the additional technical potential in electric efficiency for both the residential and

commercial sectors is considerably smaller, owing to the relatively lower upfront cost and higher


Page C-5

turnover of electric appliances and the smaller fraction of total building energy demand associated

with electrical systems (as compared to thermal systems).

This analysis points to the need for a state energy strategy to address the economically achievable

gains in thermal efficiency in the residential and commercial sectors. The substantial technical

potential in residential thermal efficiency highlights the need for flexible policies that prepare for

decreasing technology costs or rising fuel prices, either of which would increase the economic

viability of more advanced thermal efficiency measures.

Transportation Energy Efficiency

In the transportation sector, Navigant analyzed energy savings enabled by gains in light, medium, and

heavy duty vehicle fuel economy, as well as through reductions in vehicle miles traveled (VMT). The

analysis for fuel economy was informed by modifying assumptions in the vehicle stock model used to

develop the baseline forecast. Because all new vehicles could be replaced with their most efficiency

counterpart, the technical potential for fuel economy is limited only by the vehicle turnover between

2014 and 2025. In contrast, the economic potential assumes that equivalent gasoline powered stock is

only replaced with higher efficiency hybrid and electric vehicles when the breakeven period for

ownership (the time at which accumulated fuel savings offset the price premium for a more efficient

vehicle) is below 10 years (the average life of a vehicle).

The technical potential for energy savings from VMT reduction relied on the “Summary of U.S. VMT

Reduction Strategies” published by the Rocky Mountain Institute in 2011, which presents high and

low estimates of VMT reduction for several initiatives. 21

Many of the strategies are more applicable

to areas of high congestion or where alternative means of transportation exist. Given New

Hampshire’s small number of urban centers, the low-end estimate from this study was used to

estimate the technical potential for the state. The Rocky Mountain Institute divides the effects of

VMT reduction strategies into four categories: smart growth, pricing systems to discourage VMT,

alternative commuting (including car sharing, carpooling, and telecommuting), and system efficiency.

The conservative (low) estimate suggests that up to a 46 percent reduction in VMT is technically

achievable.

The economic potential was estimated using VMT reduction plans from Denver and Sacramento, as

these plans target VMT reduction levels that do not adversely impact the economy. Recognizing that

these plans are for relatively population-dense areas, the VMT reduction targets (10.0 percent and

13.2 percent respectively) were applied only to the VMT traveled by New Hampshire’s population

living in cities larger than 20,000 people. This results in an economically viable 3.9 percent reduction

in VMT. The gap analysis of these resources is illustrated in Figure 22: Potential for Transportation

Energy Efficiency.

21 Rocky Mountain Institute Summary of U.S. VMT reduction strategies available at:

http://www.rmi.org/RFGraph-Summary_of_US_VMT_reduction_strategies


Page C-6

Figure 22: Potential for Transportation Energy Efficiency

22

While the remaining economic potential is approximately the same size for the three resources

analyzed, the technical potential of both light duty fuel economy and VMT reduction strategies make

these the most promising long-term solutions to promote energy efficiency in the transportation

sector. The sizeable gaps between economic and technical potential suggests a tremendous

opportunity for savings amid rising fuel costs and falling prices for high efficiency hybrids and plug-

in electric vehicles. However, significant effort will be required to provide the necessary market

mechanisms and infrastructure to capitalize on these opportunities.

C.4 Thermal and Transportation Fuels Potential

The resource potential study for thermal and transportation fuels relied on a variety of sources

specific to each fuel considered. The fuel types are discussed individually in the following sections.

Natural Gas

Navigant’s estimates of the technical and economic potential for natural gas transmission and pipeline

expansion relied heavily on the integrated resource plans of New Hampshire’s gas utilities23,24

and a

study by ICF International titled “Assessment of Growth for National Grid’s NH Natural Gas

Utility”25

published in October 2012. These documents suggest that no large infrastructure upgrades

are expected to expand natural gas distribution networks significantly within New Hampshire over the

next decade. However, if a large natural gas distribution project for the region of New England (for

example the Northeast Expansion Project Pipeline proposal and Spectra Energy’s Atlantic Bridge

22 Source data and reports used in estimating the potential for transportation energy efficiency are detailed in C.6 Resource

Potential - Supporting Data. 23 Liberty's Integrated Resource Plan:

http://www.puc.nh.gov/Regulatory/Docketbk/2013/13-313/INITIAL%20FILING%20-%20PETITION/13-313%202013-11-

01%20ENGI%20DBA%20LIBERTY%20INTEGRATED%20RESOURCE%20PLAN.PDF 24 Northern Utilities Testimony on Integrated Resource Plan:

http://www.puc.nh.gov/Regulatory/Docketbk/2013/13-086/INITIAL%20FILING%20-%20PETITION/13-086%202013-04-

15%20NORTHERN%20UTILITIES%20TESTIMONY%20T%20MEISSNER.PDF 25 ICF - Assessment of New England’s Natural Gas Pipeline Capacity available at:

http://www.icfi.com/insights/projects/energy/assessment-of-new-england-natural-gas-pipeline-capacity


Page C-7

project) is completed during this timeframe, it could spur the development of line extensions to new

service territories within the state, increasing the technical and economic potential.

Because the future of projects such as these is uncertain, for the residential sector Navigant limited

the technical potential of natural gas consumption to residences within current service territories. The

economic potential model assumes that all on-main residences convert to natural gas, but that only 10

percent of off-main residences within the utilities’ service territories do so. The assumptions

informing natural gas expansion in the commercial sector are similar, but assume that it would be

economical to switch to gas for 30 percent of off-main businesses within the utilities’ service

territories. Because of the higher demand per customer in the commercial and industrial sections, the

barriers to gas expansion (such as upfront cost) are less significant than in the residential sector.

Unlike the residential and commercial sectors, the technical potential of natural gas consumption in

the industrial sector is not limited to existing service territories. The high demand from industrial

customers makes them an attractive target for trucked CNG, technically extending natural gas

delivery to all industry in the state. The economic potential is estimated as 50 percent of current off-

main industrial customers within the utility’s service territories and 25 percent of industrial customers

outside of current service territories.

Biomass

For biomass, the potential for thermal conversion in each sector was initially limited to the technical

potential of the sustainably harvested resource as determined using data from the Department of

Environmental Services (DES) Climate Action Plan (Appendix 8: The Wood Biomass Wedge in New

Hampshire: Data Sources and Basic Approach)26

. The technical potential was further reduced based

on thermal load and the technical fit with each sector. Because of concerns over particulate emissions

in more densely populated areas, the technical potential of biomass in the residential sector was

reduced to the fraction of the population located in rural areas (55 percent as determined using US

census data27

) and outside of the gas utilities’ service territories. Because of the current pricing of

competitive fuels, the economic potential of biomass heat in the residential sector was further limited

to the fraction of residences currently using electric heating (12 percent), fuel oil (27 percent),

propane (3 percent) and kerosene (1 percent).

In the commercial and industrial sectors, the technical potential of biomass was limited to the thermal

load of New Hampshire businesses located outside of gas utilities’ service territories. The economic

potential for these sectors was further limited to the fraction of commercial building stock constructed

before 1989 (39 percent), after which building practices favored higher efficiency systems not well

suited to conversion to biomass heat.

Ground Source Heat Pumps

Estimates of the technical and economic potential for geothermal energy in the residential and

commercial sectors in New Hampshire were informed by a Navigant study prepared for the US

Department of Energy titled "Ground Source Heat Pumps: Overview of Market Status, Barriers to

Adoption, and Options for Overcoming Barriers,”28

and interviews with ground source heat pump

installers in New Hampshire. Because of land use requirements for ground source heat pumps, the

technical potential in both sectors is limited to the space heating thermal load in less densely

populated areas, as determined using US census data (55 percent of the total)27

. The economic

potential was based on the fraction of installations that would achieve a pay-back period of less than 3

years (15 percent) as indicated by information gathered through installer interviews.

26 http://des.nh.gov/organization/divisions/air/tsb/tps/climate/action_plan/documents/032509_nhccptf_appendix_8.pdf 27 http://www.ers.usda.gov/datafiles/Rural_Definitions/StateLevel_Maps/NH.pdf 28 http://www1.eere.energy.gov/geothermal/pdfs/gshp_overview.pdf


Page C-8

Air Source Heat Pumps

The technical potential for air source heat pumps across the residential, commercial, and industrial

sectors was limited to the space heating thermal load in each sector as determined from the DOE

Building Energy Data Book32

. To account for the technical limitations of current air source heat pump

technology, Navigant used the percentage of heating degree days29

above 10º F; when the temperature

falls below 10º F, a supplemental heat source is required. In the residential sector, the economic

potential is limited by the fraction of housing stock with existing duct heating systems that are not

heated with gas, of which 75 percent are estimated to represent economically viable opportunities for

this technology.30

Without existing ducting, air source heat pumps are limited to ductless mini-split

systems. In the commercial and industrial sectors, the estimate of the economic potential follows a

similar methodology as that used for biomass, by examining the age of building stock and screening

out buildings constructed before 1960 and after 198931

.

Solar Thermal

The technical and economic potential of solar thermal was estimated using the DOE Building Energy

Data book32

and information gathered through interviews with solar thermal installers based in New

Hampshire. This estimate starts with the total residential thermal load associated with both space

conditioning and water heating and is adjusted to reflect the portion of residential buildings that have

adequate roof structure, orientation, and little or no shading (50 percent). The economic potential is

further limited to installations that are estimated to have a payback period of less than 20 years for

space heating applications and less than 5 years for water heating applications (10 percent).

Summary Results

The technical and economic potentials determined by the analysis of thermal fuels are presented in

Figure 23: Economically Justified and Technically Achievable Fuel Conversion.

29 http://www.degreedays.net/#generate, BERLIN MUNICIPAL AIRPORT, NH, US (71.18W,44.58N) 30 U.S. Energy Information Administration, Residential Energy Consumption Survey (RECS), Table HC6.8 Space Heating

in U.S. Homes in Northeast Region, Divisions, and States, 2009 http://www.eia.gov/consumption/residential/data/2009/ 31 DOE Buildings Energy Data Book, Table 3.2.4, Share of Commercial Floor space, by Census Region and Vintage, as of

2003 (Percent) http://buildingsdatabook.eren.doe.gov/ChapterIntro3.aspx 32 US DOE Buildings Energy Data Book http://buildingsdatabook.eren.doe.gov/ChapterIntro2.aspx


Page C-9

Figure 23: Potential for Thermal Fuel Adoption33

Because of the large rural population in New Hampshire located outside of gas utilities service

territory, and the relatively low cost of biomass, wood-fired heat is the most economically viable

opportunity for fuel conversion in the residential sector. In contrast, the technical requirements of the

commercial and industrial sectors, where many processes require fuels with a considerably higher

heat rate, result in significantly lower potential for additional biomass. Conversion to natural gas is

economically justified for these sectors, and trucked CNG provides opportunities for natural gas as a

source of thermal energy for off-main industries.

In addition to biomass and natural gas, existing incentives present substantial opportunities for

economically viable installations of ground and air source heat pumps in the residential sector. The

technical potential for either technology in this sector is significant and the gap between what is

economically viable and technically possible will narrow as the cost of installation drops and/or

competing fuel prices rise. Air source heat pumps also have substantial technical and economic

potential in the commercial sector. The technical potential of this technology in both the residential

and commercial sectors suggests this to be a promising opportunity as the cost of technology

decreases. This is especially important given the anticipated shift in New Hampshire’s economy from

manufacturing industries to information technology. Programs incenting the adoption of air source

heat pumps in the commercial sector should be in place throughout this period of economic

transformation to ensure that this technology is not overlooked.

Transportation Fuels

Navigant analyzed the technical, economic, and market potential for three alternative fuels in the

transportation sector: biofuels, natural gas, and electricity.

The biofuels analyzed include ethanol and bio-diesel. Bio-gasoline and bio-gas were rejected due to

uncertainty over the availability of these fuels, as they are both still largely in the development phase.

While the technical potential for biofuels is limited to some extent by fleet turnover (the rate at which

vehicles are replaced), there are also significant supply constraints for these resources. Accordingly,

the technical potential for ethanol was determined by the ratio of current production (13 billion

gallons34

) to target production for 2022 (21 billion gallons35

), or an increase in availability of 60%.

The technical potential for bio-diesel used an extrapolated forecast of biodiesel production in the US.

This forecast estimates 2025 production at roughly two times (190%) that of present day production.

These estimates were made using information from the US DOE’s Alternative Fuels Data Center36

and are based upon on the assumption that the availability of biofuels in New Hampshire follows a

similar trajectory as the rest of the US. The economic potential of both of the biofuels assumes that

ethanol consumption surpasses the E10 blend wall,37

reaching 12% of gasoline consumption by 2025,

and that diesel moves to B20 blends (20% biodiesel).

In contrast to biofuels, which are largely limited by the availability of feedstock for fuel production,

natural gas consumption in the transportation sector is limited by distribution. At present, there is

only one station offering CNG to the public in New Hampshire. However, since CNG can use

distribution infrastructure similar to existing refueling stations, this barrier will be reduced over time

as existing stations can be permitted and retrofitted to offer CNG. As such, Navigant’s estimate of

33 Source data and reports used in estimating the potential for fuel conversion are detailed in C.6 Resource Potential -

Supporting Data. 34 http://ethanolrfa.org/pages/monthly-fuel-ethanol-production-demand 35 http://www.eia.gov/forecasts/aeo/MT_liquidfuels.cfm 36 http://www.afdc.energy.gov/data/search?q=biodiesel 37 http://www.eia.gov/oog/info/twip/twiparch/100708/twipprint.html


Page C-10

the technical potential of natural gas in the transportation sector was limited only by fleet turnover.

As with the estimate of light duty vehicle fuel economy, the economic potential assumes that

equivalent gasoline powered stock is only replaced with CNG vehicles offering a payback period

below 10 years (the average life of a vehicle). The vehicle price premiums for CNG vehicles relative

to their conventional gasoline powered counterparts were taken from a presentation made to the DOE

EIA in 2013, titled “The Future of Natural Gas as a Transportation Fuel.”38

For estimates of the technical and economic potential of vehicle electrification, Navigant followed a

similar approach as for CNG, limiting the technical potential by fleet turnover, and limiting the

economic potential to the fraction of vehicles that would achieve a payback period within the 10 year

average vehicle lifetime. For both CNG and electric vehicles, Navigant did not limit the technical

potential based on availability of these vehicles in the current market, assuming that automakers and

dealers would respond to consumer demand. However, the current lack of availability of alternative

fuel vehicles in the New Hampshire market certainly presents a barrier to developing consumer

awareness and driving widespread market adoption.

Figure 24: Potential for Alternative Transportation Fuels illustrates the economic and technical

potential for alternative fuels in transportation. Based on this analysis, while biofuels offer a more

economical alternative, the magnitude of the technical potential for both natural gas and electric

vehicles makes them more attractive targets for policies to drive market adoption of alternative fuel

vehicles (AFVs).

38 http://www.eia.gov/conference/2013/pdf/presentations/gallagher.pdf


Page C-11

Figure 24: Potential for Alternative Transportation Fuels39

C.5 Power Generation & Energy Infrastructure Potential

Power Generation

All fossil fuels used for power generation in New Hampshire come from out of state. As such,

greater investment in renewable energy reduces reliance on imported fuels, fosters self-sufficiency,

and keeps spending in-state. To promote development on this front, New Hampshire adopted an RPS

in 2007. The current standard specifies the total amount of power that must be procured from all

classes is 24.8% by 2025.40

Navigant analyzed the technical and economic potential of each of the following renewable power

generation resources to examine opportunities to reduce reliance on fossil fuels for power generation.

Navigant’s estimate of the technical potential for renewable power generation utilized the National

Renewable Energy Lab (NREL) study “U.S. Renewable Energy Technical Potentials: A GIS-Based

Analysis.”41

This report presented the technical potential for installed capacity and power generation

for 11 classes of renewables, including:

Urban Utility-scale PV

Rural Utility-scale PV

Rooftop PV

Concentrated Solar Power (CSP)

Onshore Wind

Offshore Wind

Biopower-Solid

Biopower-Gaseous

Geothermal Hydrothermal

Enhanced Geothermal Systems (EGS)

Hydropower

For the purposes of the resource potential study, Navigant combined the classes of utility-scale PV

and bio-power into one class for each resource. Additionally, Navigant did not consider the technical

potential for EGS geothermal power generation. Only one plant of this type is in operation in the US,

so the future inclusion of this category will depend on further information about the suitability of

EGS technology for power generation in New Hampshire.

In light of the recent price trends for solar technology, the estimate of economic potential for solar PV

is based upon unsubsidized levels of solar development at true grid parity42

, i.e. without incentives,

but with a 20 percent utility cap, as estimated by the Institute for Local Self-Reliance. The solar PV

nameplate capacity was translated into actual power generation using the same ratio of solar PV

capacity to power generation as indicated in the NREL study of technical potential.

For biomass, the economic potential for power generation was estimated using data from the DES

Climate Action Plan (Appendix 8: The Wood Biomass Wedge in New Hampshire: Data Sources and

Basic Approach)43

and the 2012 Regional Assessment of Woody Biomass Physical Availability as an

39 Source data and reports used in estimating the potential for alternative transportation fuels are detailed in C.6 Resource

Potential - Supporting Data. 40 http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=NH09R 41 http://www.nrel.gov/docs/fy12osti/51946.pdf 42 http://www.ilsr.org/projects/solarparitymap/ 43 http://des.nh.gov/organization/divisions/air/tsb/tps/climate/action_plan/documents/032509_nhccptf_appendix_8.pdf


Page C-12

Energy Feedstock for Combined Combustion in the US Northern Region44

as published in the Journal

of Forestry. The latter study corrects for merchantability and estimates an available 738,000 metric

dry tons a year in New Hampshire. These estimates assume expansion of biomass fueled power

generation using only feedstock grown in-state.

The economic potential of terrestrial wind was informed by an NREL study titled “An Analysis of the

Technical and Economic Potential for Mid-Scale Distributed Wind,” which examines the potential for

distributed wind (smaller than utility scale) to address the needs of large commercial and industrial

customers, and potentially municipalities.45

Navigant scaled the findings of this study to address

residential demand as well. For offshore wind development, the economic potential used Cape Wind

as a reference point and scaled this value based on the relative offshore wind resources of New

Hampshire and Massachusetts.

The technical and market potentials for in-state hydroelectric power are small in comparison to other

resources (852 MW technical and 455 MW market). The economic potential for hydroelectric power

was estimated based on its ability to economically compete with other types of power generation

through the forecast period. This was estimated as the percent increase in the cost of competing fuels

for power generation through the forecast period, equating to a 10 percent increase in economically

justified in-state hydroelectric capacity. It is important to note that new hydroelectric projects, as well

as existing hydroelectric projects over 5 megawatts, do not currently qualify for the RPS.46

Figure 25: Potential for Renewable Energy Capacity

47

44 http://www.nrs.fs.fed.us/pubs/jrnl/2012/nrs_2012_goerndt_001.pdf 45 http://www.nrel.gov/wind/pdfs/midscale_analysis.pdf 46 http://www.puc.state.nh.us/sustainable%20Energy/Renewable_Portfolio_Standard_Program.htm 47 Source data and reports used in estimating the potential for alternative transportation fuels are detailed in C.6 Resource

Potential - Supporting Data.


Page C-13

Figure 26: Potential for Renewable Power Generation

47

What clearly stands out from this analysis is the magnitude of technical potential for utility scale PV

and offshore wind makes them especially attractive as the cost of technology comes down. The

analysis also shows significant remaining technical potential for midscale terrestrial wind and

rooftop PV. Given the relative capacity factors for wind and solar, the remaining economic potential

for additional terrestrial wind power generation is actually higher than that of either solar technology

making continued development of these resources the most economically viable opportunity to

expand in-state renewable power generation in the near term. As electric rates rise, and additional

attention is given to distributed generation as a means to foster grid reliability, a policy landscape that

fosters innovation will play a critical role in helping all of these resources achieve their full economic

potential.

Electric Infrastructure

Two resources were analyzed within the electric infrastructure category: combined heat and power

(CHP) and electric storage. It should be noted that these resources are not in competition with one

another, as they provide significantly different benefits. CHP capitalizes on collocated electric and

thermal loads, generating both electric power and thermal energy. In contrast, electric storage

provides a variety of benefits including load shifting, frequency regulation, and backup power, as well

as helping with the integration of intermittent renewable resources with the grid.

The technical potential for CHP in New Hampshire was estimated using information gained from a

report on CHP for Commercial Buildings Benefits Analysis prepared by Arthur D. Little, Inc.48

It was

estimated that 25% of the target sectors’ (commercial and industrial) thermal and electric loads were

collocated in a way that CHP would provide benefits. The economic potential was further limited to

only those applications with adequate scale to justify installation. Current CHP installations in New

Hampshire vary from 10 kilowatts to 12 megawatts and are fueled by oil (50% of capacity), natural

gas (40% of capacity) and wood (10% of capacity)49

.

48 https://www1.eere.energy.gov/manufacturing/distributedenergy/pdfs/chp_benefits_commercial_buildings.pdf 49 http://www.eea-inc.com/chpdata/States/NH.html


Page C-14

The estimate of technical potential for electric storage was based on the economic benefits of daily

load smoothing. Load smoothing helps reduce the cost of peak electricity by shifting loads away

from times of peak demand. This is accomplished by storing power generated during off-peak times,

and deploying this stored power during peak events. Using historical data from ISO New England50

,

one half of the difference between the average minimum and maximum daily demand was used to

estimate the total storage needed to smooth loads. To estimate the economic potential, Navigant

examined energy storage as it is typically deployed. At present, most electric storage is economically

justified based on its ability to smooth loads attributed to intermittent resources. In markets with

significant renewable power generation, intermittent resources are firmed with storage at 25 percent

of nameplate capacity. This figure was applied to the baseline forecast for renewables in New

Hampshire and served as the basis for the estimated economic potential of electric storage. The

amount of storage required will increase with greater deployment of renewable power generation.

Figure 27: Electric Infrastructure Capacity

51

As indicated in Figure 27: Electric Infrastructure Capacity, the technical and economic potential for

CHP systems surpasses the potential for electric storage. This can be attributed to the clear economic

benefits of efficiency gains with CHP systems, compared to the benefits of storage which are more

difficult to quantify and are affected by the limited penetration of renewable power generation in-

state. However, additional gains in storage technology are important for reducing costs during peak

usage times and balancing intermittent renewables.

The economic and technical potentials of these infrastructure technologies, and those of the

renewable power generation resources, will help guide policy development by highlighting the most

significant opportunities for further resource development.

50 http://www.iso-ne.com/markets/hst_rpts/hstRpts.do?category=Hourly 51 Source data and reports used in estimating the potential for alternative transportation fuels are detailed in C.6 Resource

Potential - Supporting Data.


Page C-15

C.6 Resource Potential - Supporting Data

Resource Potential Source Data

Report / Data Set Web Address

GDS Associates, Inc.,“Additional

Opportunities for Energy Efficiency

in New Hampshire,”

http://www.puc.state.nh.us/Electric/GDS%20Report/NH%20Additiona

l%20EE%20Opportunities%20Study%202-19-09%20-%20Final.pdf

DOE: Building Energy Data Book http://buildingsdatabook.eren.doe.gov/

2013 ORNL Energy Data Book http://cta.ornl.gov/data/index.shtml

Idaho National Laboratory EV

Project Data http://avt.inel.gov/evproject.shtml

Federal Highway Authority Fleet

Statistics https://www.fhwa.dot.gov/ohim/onh00/onh2p3.htm

Rocky Mountain Institute, Summary

of U.S. VMT reduction strategies

http://www.rmi.org/RFGraph-

Summary_of_US_VMT_reduction_strategies

Table 3: Energy Efficiency Resource Potential Source Data


Page C-16


Unitil Gas Rates http://unitil.com/energy-for-residents/gas-information/rates

http://unitil.com/energy-for-businesses/gas-information/rates

National Grid: Renewable Gas Vision for

a Sustainable Gas Network http://www.nationalgridus.com/non_html/ng_renewable_wp.pdf

EnergyNorth Natural Gas: Integrated

Resource Plan

http://www.puc.nh.gov/Regulatory/Docketbk/2013/13-

313/INITIAL%20FILING%20-%20PETITION/13-313%202013-

11-

01%20ENGI%20DBA%20LIBERTY%20INTEGRATED%20RES

OURCE%20PLAN.PDF

Northern Utilities, Inc. Testimony http://www.puc.nh.gov/Regulatory/docketbk-2013.html

United States Census Bureau State &

County QuickFacts:

New Hampshire

http://quickfacts.census.gov/qfd/states/33000.html

Massachusetts Department of Energy

Resources: Commonwealth Accelerated

Renewable Thermal Strategy

http://www.mass.gov/eea/docs/doer/renewables/thermal/carts-

report.pdf

Navigant Report on Ground‐Source Heat

Pumps: Overview of Market Status,

Barriers to Adoption, and Options for

Overcoming Barriers

http://www1.eere.energy.gov/geothermal/pdfs/gshp_overview.pdf

USDA: Economic Research Service:

Atlas of Rural and Small-Town America

http://www.ers.usda.gov/datafiles/Rural_Definitions/StateLevel_M

aps/NH.pdf

DOE Energy Saver:

Active Solar Heating http://energy.gov/energysaver/articles/active-solar-heating

EIA: Residential Energy Consumption

Survey 2009 & Commercial Buildings

Energy Consumption Survey 2012

http://www.eia.gov/consumption/residential/data/2009/

DOE: Building Energy Data Book http://buildingsdatabook.eren.doe.gov/

WeatherUnderground.com /

DegreeDays.net

http://www.degreedays.net/#generate, BERLIN MUNICIPAL

AIRPORT, NH, US (71.18W,44.58N)

DOE Alternative Fuels Data Center http://www.afdc.energy.gov/

Renewable Fuels Association:

Monthly U.S. Fuel Ethanol

Production/Demand

http://ethanolrfa.org/pages/monthly-fuel-ethanol-production-

demand

2013 ORNL Energy Data Book http://cta.ornl.gov/data/index.shtml

Idaho National Laboratory:

EV Project Data http://avt.inel.gov/evproject.shtml

Federal Highway Authority:

Fleet Statistics https://www.fhwa.dot.gov/ohim/onh00/onh2p3.htm

Table 4: Alternative Fuels Resource Potential Source Data


Page C-17


NREL: U.S. Renewable Energy

Technical Potentials: A GIS-Based

Analysis

http://www.nrel.gov/gis/re_potential.html

Institute for Local Self Reliance:

Commercial Rooftop

Revolution

http://www.ilsr.org/commercial-roofop-revolution/

Interstate Renewable Energy

Council: National Report on Solar

Installation Trends

http://www.irecusa.org/2013/07/national-report-on-solar-installation-

trends-offers-insight-and-analysis/

DOE: WINDExchange –

Wind Resource Potential

http://apps2.eere.energy.gov/wind/windexchange/windmaps/resource_

potential.asp

NREL: An Analysis of the Technical

and Economic Potential for Mid-

Scale Distributed Wind

http://www.nrel.gov/wind/pdfs/midscale_analysis.pdf

WindAction: U.S. Average Annual

Capacity factors by project and State

http://www.windaction.org/posts/37255-u-s-average-annual-capacity-

factors-by-project-and-state#.U_uZ1vldWSq

NREL: Offshore Wind Resource

Characterization http://www.nrel.gov/wind/offshore_resource_characterization.html

CapeWind http://www.capewind.org/index.php

DES: New Hampshire Climate

Action Plan

http://des.nh.gov/organization/divisions/air/tsb/tps/climate/action_plan/

documents/032509_nhccptf_appendix_8.pdf

USDA Forest Service Journal of

Forestry: Regional Assessment of

Woody Biomass Physical

Availability as an Energy Feedstock

for Combined Combustion in the US

Northern Region.

http://www.nrs.fs.fed.us/pubs/jrnl/2012/nrs_2012_goerndt_001.pdf

ICF: Combined Heat and Power

Units located in New Hampshire http://www.eea-inc.com/chpdata/States/NH.html

ISO-NE Pricing and Energy, Load,

and Demand Reports

http://www.iso-

ne.com/isoexpress/web/reports/pricing?category=Hourly

http://www.iso-ne.com/isoexpress/web/reports/load-and-demand/-

/tree/net-ener-peak-load

Table 5: Power Generation & Energy Infrastructure Resource Potential Source Data


Page C-18

Resource Potential Data Tables

Subsector - Resource Units Technical Economic BAU

Residential - Thermal Efficiency BBtu 22,300 8,322 4,789

Residential - Electric Efficiency BBtu 4,816 3,183 1,898

Industrial - Thermal Efficiency BBtu 1,701 1,372 663

Industrial - Electric Efficiency BBtu 2,744 2,357 1,138

Commercial - Thermal Efficiency BBtu 7,463 4,803 2,026

Commercial - Electric Efficiency BBtu 4,525 3,021 1,393

Table 6: Electric and Thermal Energy Efficiency Resource Potential Data (BBtu Savings)

Resource Units Technical Economic BAU

Medium & Heavy Duty Vehicles BBtu 10,516 4,217 456

Light Duty Vehicles BBtu 57,377 22,758 18,284

VMT Reduction BBtu 41,370 3,516 (708)

Table 7: Transportation Energy Efficiency Resource Potential Data (BBtu Savings)


Commercial - Ground Source HP BBtu 4,612 231 -

Residential - Solar Thermal BBtu 8,920 892 9

Commercial - Biomass BBtu 5,647 2,199 1,132

Industrial - Biomass BBtu 3,419 1,331 40

Residential - Air Source HP BBtu 31,388 6,173 4,764

Commercial - Natural Gas BBtu 24,481 15,087 13,562

Industrial - Air Source HP BBtu 7,398 2,880 796

Residential - Natural Gas BBtu 19,820 11,144 8,469

Commercial - Air Source HP BBtu 19,515 7,598 4,412

Residential - Ground Source HP BBtu 22,078 3,312 33

Industrial - Natural Gas BBtu 15,194 12,589 9,190

Residential - Biomass BBtu 24,531 10,732 6,467

Table 8: Alternative Thermal Fuels Resource Potential Data (BBtu)


Page C-19


Electric % 88.3% 5.7% 1.9%

Natural Gas % 90.1% 4.1% 0.2%

Biofuel % 15.8% 11.8% 6.5%

Table 9: Alternative Transportation Fuels Resource Potential Data (% of demand)


Utility Scale Solar PV GWh 61,154 635 34

Offshore Wind GWh 14,478 270 -

Terrestrial Wind GWh 5,706 1,612 835

Rooftop Solar PV GWh 2,299 635 34

Biomass GWh 2,097 1,938 1,780

Hydroelectric GWh 1,741 1,157 1,052

Table 10: Renewable Energy Generation Resource Potential Data (GWh)


Utility Scale Solar PV MW 37,928 394 16

Offshore Wind MW 3,456 76 -

Terrestrial Wind MW 2,135 492 304

Rooftop Solar PV MW 2,062 570 16

Hydroelectric MW 753 501 455

Biomass MW 747 358 304

Table 11: Renewable Energy Capacity Resource Potential Data (MW)


Electric Storage MW 376 80 47

Combined Heat and Power MW 1,173 499 59

Table 12: Energy Storage and CHP Resource Potential Data (MW)

Documents

Appendix A. Baseline Energy Forecast - NH.gov - The ... · PDF fileAppendix A. Baseline Energy Forecast ... 4 ISO-NE 2013 Regional System Plan –Section 1.2 Overview of the Results